Older Drivers and Navigation Devices
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Summary
This study, conducted by the National Highway Traffic Safety Administration, investigated the impact of electronic navigation systems (ENS) on the driving performance of older adults. The research was motivated by age-related declines in cognitive and psychomotor abilities, which complicate wayfinding and route learning. While ENS technology could theoretically offset these deficits, prior literature indicated low adoption rates among older drivers due to concerns about complexity and distraction. The study aimed to determine if ENS use improves driving performance compared to paper directions, how age and prior familiarity affect performance, and whether specific training can mitigate difficulties in programming the devices. The research comprised two phases involving on-road driving tests and laboratory tasks. Phase 1 included 80 participants aged 60–79, categorized by age group (60s vs. 70s) and ENS familiarity. Participants completed four drives: one to a familiar destination without aids, two on new routes using either paper directions or an ENS, and one longer route using the ENS. A driving rehabilitation specialist scored performance using a modified Miller Road Test, while GPS trackers monitored route adherence. Participants also performed manual destination entry tasks in a laboratory setting. Phase 2 involved 40 ENS-unfamiliar participants aged 60 and older, randomly assigned to receive either video-based ENS training or a placebo training program. These participants then completed destination entry tasks and on-road drives using the ENS. Phase 1 results demonstrated that all participants exhibited significantly better driving performance (lower error scores) when using the ENS compared to paper directions. However, performance varied by demographic factors: drivers in their 60s and those previously familiar with ENSs performed better than their counterparts in their 70s or those unfamiliar with the technology. Regarding route adherence, drivers in their 70s were significantly more likely to go off-route than those in their 60s, regardless of the navigation aid used. Manual destination entry accuracy was also significantly predicted by age and familiarity, with 60-year-old ENS-familiar users achieving the highest success rates (90%) and 70-year-old ENS-unfamiliar users the lowest (41.7%). Phase 2 findings revealed that while ENS training significantly improved manual destination entry accuracy (51.7% for trained vs. 40.6% for placebo), it did not improve on-road driving performance or route-following metrics. The study concludes that while ENSs can enhance driving performance for older adults by reducing the cognitive load associated with paper maps, this benefit is contingent on the user’s ability to correctly program the device. Older drivers, particularly those aged 70 and above with no prior experience, struggle significantly with manual destination entry. Although targeted training can improve programming accuracy, it does not translate to better driving behavior. The authors suggest that as technology evolves, further research is needed to determine how best to prepare older drivers for interacting with navigation systems and future semi-autonomous vehicle features.
Key finding
Older drivers exhibited better driving performance scores when using electronic navigation systems compared to paper directions, but training only improved manual destination entry accuracy without affecting driving performance.
Methodology
mixed_methods
Sample size: 120
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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- Methodological Resource: validation psychometrics, tool software